{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:TEEG3KSDMXI56IC37ASVTE2XWY","short_pith_number":"pith:TEEG3KSD","canonical_record":{"source":{"id":"2112.08596","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-12-16T03:44:01Z","cross_cats_sorted":[],"title_canon_sha256":"89b357b23cf4ced9f58b42f305bdfa30efc478ae0573c5310e10ebf5b368a135","abstract_canon_sha256":"c5f42ef309009c2ff57c0bb90e6d1a04e9ee0629cbcc7b71e43462ed24a34752"},"schema_version":"1.0"},"canonical_sha256":"99086daa4365d1df205bf825599357b63746c644aa9f7db3e491c983891e308f","source":{"kind":"arxiv","id":"2112.08596","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2112.08596","created_at":"2026-07-05T04:23:06Z"},{"alias_kind":"arxiv_version","alias_value":"2112.08596v2","created_at":"2026-07-05T04:23:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2112.08596","created_at":"2026-07-05T04:23:06Z"},{"alias_kind":"pith_short_12","alias_value":"TEEG3KSDMXI5","created_at":"2026-07-05T04:23:06Z"},{"alias_kind":"pith_short_16","alias_value":"TEEG3KSDMXI56IC3","created_at":"2026-07-05T04:23:06Z"},{"alias_kind":"pith_short_8","alias_value":"TEEG3KSD","created_at":"2026-07-05T04:23:06Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:TEEG3KSDMXI56IC37ASVTE2XWY","target":"record","payload":{"canonical_record":{"source":{"id":"2112.08596","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-12-16T03:44:01Z","cross_cats_sorted":[],"title_canon_sha256":"89b357b23cf4ced9f58b42f305bdfa30efc478ae0573c5310e10ebf5b368a135","abstract_canon_sha256":"c5f42ef309009c2ff57c0bb90e6d1a04e9ee0629cbcc7b71e43462ed24a34752"},"schema_version":"1.0"},"canonical_sha256":"99086daa4365d1df205bf825599357b63746c644aa9f7db3e491c983891e308f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:23:06.599851Z","signature_b64":"7Upet7AOP9KxnNek6J54gG+m+giHKrvCUG07yRS6QG+T4DcyCdauSijR+x6OdPtH9PWJSJiAv6JMb/rFewo9DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"99086daa4365d1df205bf825599357b63746c644aa9f7db3e491c983891e308f","last_reissued_at":"2026-07-05T04:23:06.599425Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:23:06.599425Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2112.08596","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:23:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HklZFfep/rfF4VKNQzyo35TV1pWDoxFEGsuKx0JSi4d6TGGIwXwsgYqvz7CyoY45gpzP5AmRj2V4b5l/pGXqBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-22T00:15:42.956375Z"},"content_sha256":"e89c6fd9fe85235da9d8199ab816c028db70c04a5fe052df4928478f5df424c6","schema_version":"1.0","event_id":"sha256:e89c6fd9fe85235da9d8199ab816c028db70c04a5fe052df4928478f5df424c6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:TEEG3KSDMXI56IC37ASVTE2XWY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Guiding Neural Story Generation with Reader Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Amal Alabdulkarim, Harshith Kayam, Kaige Xie, Mark O. Riedl, Samihan Dani, Xiangyu Peng","submitted_at":"2021-12-16T03:44:01Z","abstract_excerpt":"Automated storytelling has long captured the attention of researchers for the ubiquity of narratives in everyday life. However, it is challenging to maintain coherence and stay on-topic toward a specific ending when generating narratives with neural language models. In this paper, we introduce Story generation with Reader Models (StoRM), a framework in which a reader model is used to reason about the story should progress. A reader model infers what a human reader believes about the concepts, entities, and relations about the fictional story world. We show how an explicit reader model represen"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2112.08596","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2112.08596/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:23:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dkL3svP1y1p38+M9txHHiOCNBxCSskTAHB9m882dDRR1u69BODMe4bVat7DyLPROqUxf7Zuf6mOZBVFcYLivCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-22T00:15:42.956736Z"},"content_sha256":"7600013c5d981512fe38bedf8a7a3adbd707c5f741934ace83546dc22840b87b","schema_version":"1.0","event_id":"sha256:7600013c5d981512fe38bedf8a7a3adbd707c5f741934ace83546dc22840b87b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TEEG3KSDMXI56IC37ASVTE2XWY/bundle.json","state_url":"https://pith.science/pith/TEEG3KSDMXI56IC37ASVTE2XWY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TEEG3KSDMXI56IC37ASVTE2XWY/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-07-22T00:15:42Z","links":{"resolver":"https://pith.science/pith/TEEG3KSDMXI56IC37ASVTE2XWY","bundle":"https://pith.science/pith/TEEG3KSDMXI56IC37ASVTE2XWY/bundle.json","state":"https://pith.science/pith/TEEG3KSDMXI56IC37ASVTE2XWY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TEEG3KSDMXI56IC37ASVTE2XWY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:TEEG3KSDMXI56IC37ASVTE2XWY","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"c5f42ef309009c2ff57c0bb90e6d1a04e9ee0629cbcc7b71e43462ed24a34752","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-12-16T03:44:01Z","title_canon_sha256":"89b357b23cf4ced9f58b42f305bdfa30efc478ae0573c5310e10ebf5b368a135"},"schema_version":"1.0","source":{"id":"2112.08596","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2112.08596","created_at":"2026-07-05T04:23:06Z"},{"alias_kind":"arxiv_version","alias_value":"2112.08596v2","created_at":"2026-07-05T04:23:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2112.08596","created_at":"2026-07-05T04:23:06Z"},{"alias_kind":"pith_short_12","alias_value":"TEEG3KSDMXI5","created_at":"2026-07-05T04:23:06Z"},{"alias_kind":"pith_short_16","alias_value":"TEEG3KSDMXI56IC3","created_at":"2026-07-05T04:23:06Z"},{"alias_kind":"pith_short_8","alias_value":"TEEG3KSD","created_at":"2026-07-05T04:23:06Z"}],"graph_snapshots":[{"event_id":"sha256:7600013c5d981512fe38bedf8a7a3adbd707c5f741934ace83546dc22840b87b","target":"graph","created_at":"2026-07-05T04:23:06Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2112.08596/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Automated storytelling has long captured the attention of researchers for the ubiquity of narratives in everyday life. However, it is challenging to maintain coherence and stay on-topic toward a specific ending when generating narratives with neural language models. In this paper, we introduce Story generation with Reader Models (StoRM), a framework in which a reader model is used to reason about the story should progress. A reader model infers what a human reader believes about the concepts, entities, and relations about the fictional story world. We show how an explicit reader model represen","authors_text":"Amal Alabdulkarim, Harshith Kayam, Kaige Xie, Mark O. Riedl, Samihan Dani, Xiangyu Peng","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-12-16T03:44:01Z","title":"Guiding Neural Story Generation with Reader Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2112.08596","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:e89c6fd9fe85235da9d8199ab816c028db70c04a5fe052df4928478f5df424c6","target":"record","created_at":"2026-07-05T04:23:06Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"c5f42ef309009c2ff57c0bb90e6d1a04e9ee0629cbcc7b71e43462ed24a34752","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-12-16T03:44:01Z","title_canon_sha256":"89b357b23cf4ced9f58b42f305bdfa30efc478ae0573c5310e10ebf5b368a135"},"schema_version":"1.0","source":{"id":"2112.08596","kind":"arxiv","version":2}},"canonical_sha256":"99086daa4365d1df205bf825599357b63746c644aa9f7db3e491c983891e308f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"99086daa4365d1df205bf825599357b63746c644aa9f7db3e491c983891e308f","first_computed_at":"2026-07-05T04:23:06.599425Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:23:06.599425Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"7Upet7AOP9KxnNek6J54gG+m+giHKrvCUG07yRS6QG+T4DcyCdauSijR+x6OdPtH9PWJSJiAv6JMb/rFewo9DA==","signature_status":"signed_v1","signed_at":"2026-07-05T04:23:06.599851Z","signed_message":"canonical_sha256_bytes"},"source_id":"2112.08596","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e89c6fd9fe85235da9d8199ab816c028db70c04a5fe052df4928478f5df424c6","sha256:7600013c5d981512fe38bedf8a7a3adbd707c5f741934ace83546dc22840b87b"],"state_sha256":"987bf56d0fb905aa206b376f6b37b2108a1505966220e69a9f0d38a77aa130f3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+DXDSUxQCndWoGSbdyU0pZ+wuTkWj9KkG5SW4kcxdTLi97+CgxbRDtH/WoDajX5LQSqKrcq1rzv6bnHlLFZiCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-22T00:15:42.958810Z","bundle_sha256":"427a7ead86beacb7a1c82e768081c66616a49ad00078507b8271e56c53387e95"}}